The deployment of moving sensor platforms (e.g., self-driving cars, drones, and other instances) with advanced sensing is rapidly increasing the capture of human features at unprecedented temporal and spatial scales, especially in cities. This thesis advances knowledge on extracting information from this novel data source for traffic research and practice, while highlighting implications for privacy and beyond. Findings provide insights for traffic control and management, policy development, and anyone involved in responsible urban innovation.@en

This research provides insight into ways to increase accessibility for Planned Special Events (PSEs) via discrete choice modelling. A special focus within this study is put into the AFAS AZ Stadium in Alkmaar. During the events held at the AFAS AZ Stadium disturbances are experienced by its visitors with regard to crowding levels and access/egress times. Quantifying the traffic volume on the infrastructure around the venue is done via revealed preference methods. Cyclists are counted via pneumatic tubes. Whereas pedestrians are measured via radio-wave sensors. To find ways to mitigate these problems, interviews are held with organisers of similar PSEs within The Netherlands.

To find the effectiveness of the obtained accessibility measures a stated preference study is held. From this study it is obtained that the transportation mode habit that one has is a key factor within the mode choice. Besides the effect on accessibility additional decision factors are discussed to find the best measure which can be applied best at the AFAS AZ Stadium. Based on the decision factors and the performance of the accessibility measures a total of six effective measures are determined.

Cycling has gained popularity worldwide, but little is known about the choice behaviour of people searching for a bicycle parking spot in the city centre. Formal parking spaces provided in the city centre are currently often underutilised, whilst many people use fly parking, which causes nuisance. This thesis aims to identify the most effective communication strategy to reduce the utilisation of fly parking and whether this differs for distinct user groups. Traffic signs were chosen as a means to present the different communication strategies. Information on choice behaviour was gathered with the use of a stated preference survey. Discrete choice modelling was used to analyse this data. The results show communication prohibiting the use of fly parking work very effectively in reducing fly parking. Interactions of socio-demographics and communication strategies were also found, indicating that belonging to a certain user group affects the effectiveness of the different communication strategies. What should be noted is that the effect of the interactions is marginal compared to the effect of the communication strategy itself. Meaning that the effectiveness of the communication strategy itself is most important. The research also tested how well traffic signs performed as a means of delivering the communication. It was concluded that solely showing traffic signs without providing any prior or other information is not very effective.

Comparing the performance of distribution functions and a discrete choice model, on a mode & destination choice in a tour-based model. An discrete choice model is composed for a tour-based model. Both choice models are implemented in a large-scale tour-based model and the performances are compared.

Increased complexity on the waterway asks for more insight into distances between vessels. A method is created to determine the ship domain in a port area based on AIS data analysis. The method includes location, encounter types, relative position and ship-specific parameters.

The aim of this research is to develop a transport model that is able to identify potential conflicts and bottlenecks for nautical recreational activities in the IJburgbaai, an open-space water area in the eastern part of Amsterdam.

This study has investigated the effect of the urban environment on pedestrian route choice behaviour, for walking routes to and from train stations in the Netherlands. To the best knowledge of the author, this is the first pedestrian route choice study which is performed at country-level scope. This was made possible by applying an innovative quasi-revealed preference approach. Respondents self-reported their route preferences through an online GIS survey. Outputs were subsequently analysed by overlaying route data with a range of open geodata sources and searching for statistical similarities between certain urban features and (in)frequently taken routes. Results from statistical testing are verified by testing these against a qualitative text-coding analysis. The study finds that pedestrians in the Netherlands have a strong preference for the route which they perceive to be fastest, especially when they are en-route to a train station. Pedestrians dislike features which they perceive as ’slowing’ them down such as traffic lights. Detours are found somewhat more often on from-station routes, with such detours leading via environments which are attractive for social reseasons such as shops or busy streets. The method was found to work fairly well and should now be tested on a larger population sample with more variables.

This thesis constitutes a first step towards measuring the passenger capacity of station platforms. First, it defines platform capacity on the basis of the locations of queues at exit escalators from platforms, the presence of passengers in the platform-edge danger zone and the duration of stops. It then renders capacity measurable using real-life data covering train stops and passenger behaviour on platforms.@en

In the Netherlands, the bicycle is a popular means of transport. One of the benefits of cycling is improved health due to more physical activity. However, cycling also causes a health burden due to the many cycling accidents in the Netherlands. The share of single bicycle accidents, where no collision with another road user is involved, has increased over the past years. In 2000 only 10% of all bicycle accidents were single bicycle accidents, while in 2018 this increased to 35%. One of the potential causes for single bicycle accidents is narrow bicycle paths. This research focussed on the influence of the bicycle path width of narrow bidirectional bicycle paths on steering behaviour, which can support a discussion on the required minimum width for bicycle paths in the guidelines. A controlled experiment is conducted to collect data of steering behaviour variables on different bicycle path widths while controlling other influencing factors. The results of the experiment show that cyclists cycle significantly closer to the path edge on narrower bicycle paths (55.6 centimeter on a 2-meter wide path and 37 centimeter on a 1-meter wide path), while there are no differences in average steering angle. An oncoming cyclist, which is in the experiment represented by a parked bicycle, forces cyclists to cycle even closer to the path edge, which makes the minimum distance to the path edge smaller. The minimum distance to the path edge becomes 15.1 centimeter on a 1.5-meter wide path. This smaller distance to the path edge increases the risk of riding off the path, which makes the narrower paths less safe. A questionnaire was used to examine the perception of the different path widths. The perceived safety of cyclists decreased on narrower bicycle paths. A 2-meter wide bidirectional bicycle path is considered safe to pass others by all participants, but on a 1.5-meter wide path this is only considered safe by half of the participants. The main research question was “What is the influence of the width of bidirectional bicycle paths on cyclists’ steering behaviour?”. It can be concluded that lateral position is related to the width of bidirectional bicycle paths, while steering angle rotation is not related to the width of bicycle paths. The results of the experiment are transferable to real-life traffic conditions, but do not include the variety in infrastructural conditions, cyclist ages and bicycle types. These varieties in real-life traffic conditions might increase the required bicycle path width.

This research investigates the speed behaviour and safety effects on cyclists and mopeds sharing the cyclist T-Intersection with and without the application of a lane marking nudge. Unsignalised cyclist T-Intersection gives rise to more safety-critical instances, which include unsafe braking and evasive maneuvers. It is also found that uncontrolled T-intersection can create an issue when priority is assigned to the intersecting (right) arm because drivers on the straight road have a high perception of priority and fail-to-yield. Even though many studies have analysed the positive influence of the lane markings for cars, the influence of it on cyclists have not been explored. The safety criticality in this research is investigated using critical deceleration and jerk as Surrogate Safety Measures, because they are found to perform better at identifying potential conflicts compared to other time proximity measures, such as Time to Collision. Based on the results, the nudge did not show any strong evidence for reducing the speeds or safety criticality at the T-Intersection. So, it cannot be implemented as a traffic calming measure at the T-intersection without further research or modifications. So, this research also suggests key improvements with the lane marking nudge, and some crucial changes have to be implemented to avoid these kinds of unexpected outcomes in future. So, an elaborate discussion is made on what could be the possible changes with the implementation of the nudge for further investigations. Few intervention functions from the MINDSPACE framework and improvements from the behavioural change wheel have to be considered in the future researches with nudges.

With the increasing popularity of active modes (mainly pedestrians and bicycles), the spaces shared amongst these modes are also rising. Such spaces are often referred to as shared spaces and can often be seen in public areas near train stations, shopping streets and educational institutions. Such spaces are said to enhance safety and resolve spatial limitations of the space while the users are seen to exhibit interesting and complex behaviours as they freely interact with different modes approaching from various directions. This creates a need to collect data and understand the behaviour of people within such spaces.
Many studies focusing on shared space interactions are limited by the current methods of data collection and data extraction. Other studies on people movement also face similar issues. Current data extraction approaches using cameras include repetitive and labour-intensive tasks which makes them costly and inefficient. Thus, this study focuses on automating the data extraction approach to obtain the ground-plane trajectories of people using the data recorded from a 3D-stereo vision camera. The data processing framework was divided into three main stages, (i) agent detection, (ii) ground-plane representation and (iii) agent tracking. The agent detection uses a neural-network-based detection model to detect people on the visual video which is then paired with the depth data to represent people on the ground plane. Each person is represented as a single point on the ground plane for every frame of the video. These points were then inputted into a tracking model to provides trajectories of people on the ground plane. Overall, this research integrates the recent state-of-the-art technologies into a single framework to automate the data extraction process and tests this framework in a real-world setting (behind the Amsterdam central station’s shared space area). For each stage, the advantages, challenge and recommendation for further improvements have been made. By automating the data processing of real-world datasets (including pedestrians and cyclists), This study reduces the cost and provides an easy way to collect and process data on real-world movements of pedestrians and cyclists. This will encourage urban planners to better understand people’s movement within their spaces and facilitate data-driven design approaches in the future.

The increase of ship traffic flow, densities, ship size, and the uncertainty from technological advancement raise issues in traffic safety and efficiency. In order to tackle the issue, currently, a simulation model is widely used by various users as the port authority and bridge team and for research and development team. Since the issues are varied for each modeling user, the modeling purposes are also different among the users. Therefore, this research aimed to find the insight into modeling paradigms in simulating the vessel dynamic kinetic information (position, speed, course, and heading) and the encountering (overtaking, head-on, and crossing). A requirement of both aspects for each modeling purposes is set based on the simulation output needed. The insight is gained through comparison of models of the dynamic kinetic information and the encounters in six paradigms. The paradigms are Cellular Automata (CA), Generic Rule-Based (GRB), Specific Rule-Based Model (SRB), Artificial Potential Field (APF), Optimal Control (OC), and System Dynamics (SD). This research also provides an extension of the model by Shu et al. (2015a, 2015b, 2018) with OC paradigm to serve as the safety assessment for the port authority.

This thesis covers the research of a new methodology that is able to create crowd management measures for hubs that are under (re)construction where business is performed as usual. The methodology contains the steps required to perform a case analysis and use the information gathered to create and deliver practicle, feasible and efficient crowd management measures. This report covers the results of: a literature study, feedback by unstructured interviews, defined methodology based on the principles of product design, case study results of the methodology application performed at Rotterdam The Hague Airport and, assessment of the created methodology and delivered crowd management measures.

In this study, a context-dependent discrete choice model to investigate cyclist’s preferences on link-level cycling infrastructure design features is to investigate the extent the preferences on cycling infrastructure design is affected by the
characteristics of a road segment. Stated preference experiment utilizing visual representation of the alternatives were conducted. The model estimation indicates that cyclists attach different values on certain design features of a cycling infrastructure under different urban contexts. Nevertheless, there are significant heterogeneity on the preferences across respondents which still cannot be explained by the variation of contexts. Segmenting the data based on personal characteristic attributes, we found that differences in traveler’s personal characteristics are associated with certain differences in valuation of design features and also in sensitivity toward context effects.

Public transportation ridership has grown significantly over the past decades and this growth is expected to continue into the future. Crowding at train and metro stations is therefore experienced more frequently, resulting in safety issues, decreased comfort levels, increased total travel times and modality shifts. On the long term large infrastructural changes can be considered to increase the capacity but for the short term more flexible and cheaper crowd management measures can be applied. Little scientific research has been dedicated to study
the effects of crowd management measures or when to apply them. The aim of this thesis is to design a method to systematically select and assess effective crowd management measures to increase the safety and throughput in train and metro stations.

A list of 29 crowd management measures, their field of application, possible effect, characteristics and indication of costs is composed based on literature, experts or previous applications. A framework is developed to provide a means to select crowd management measures to apply at a particular train or metro station. This framework includes an applicability check, problem analysis, measure selection, assessment method and evaluation. The framework is applied on a fictional metro station, with many similarities to the Amsterdam metro. The measures that are selected using the framework have a positive effect on the safety and throughput, as indicated by the level of service and travel times. The framework is believed to help guide towards suitable measures in the multi-disciplinary decision making process.

As an increasing number of people work in office buildings and new sophisticated sensor technologies become available there is, both, a need and potential, to develop more complex building service controls that increase the energy efficiency of buildings as well as the well-being of employees. The data required for the testing and evaluation of such control systems is usually in the form of movements and locations of office building occupants collected over long periods of time. However, such data is generally difficult to obtain for reasons ranging from the need to evaluate un-commissioned buildings to privacy concerns related to data sharing. Therefore, this study develops a pedestrian behaviour model that can simulate office occupants’ movements and locations thereby acting as a research platform that produces data for external applications. The model is integrated as it simulates not only the movements of occupants between different locations in the building but also decisions that drive the movements such as which activities occupants want to carry out throughout the day, and when and where they want to perform these activities. Furthermore, the model is based on the guidelines of (i) flexibility – the model is able to simulate movements in different building plans and represent movement patterns of different organizations; (ii) extensibility – the model uses a modular framework that enables easy adoption of more complex components and integration with other workplace related studies as and when required; and (iii) data parsimony – the model has low and simple data requirements itself.

With the development of the inland waterway transport, ship locks become more and more important as infrastructure in waterway network. Currently, there are a lot of studies about the capacity of locks, but the impact of the chamber’s horizontal dimension on the passing time and the costs-benefits should be studied more. In order to study the method of selecting optimum scenarios of enlarging locks, Eefde lock is taken as a case. The thesis is aimed to determine the optimum enlargement scenario for the Eefde lock. Furthermore, the relationship between the horizontal dimension of chambers and costs-benefits is also found and suggestions are given to other locks with insufficient capacity. In the thesis, different scenarios are made at first, and then SIVAK (Simulation model for Waterways and Infrastructure) is used for simulations. The study finds that the enlargement of width is more effective to reduce waiting time than the enlargement of the chamber’s length. After the study of the Eefde lock, approach to the optimum enlargement scenarios is generalized for other locks.